A5101860238- Atmospheric aerosols and clouds
- Atmospheric chemistry and aerosols
- Atmospheric and Environmental Gas Dynamics
- Advanced Numerical Methods in Computational Mathematics
- Aeolian processes and effects
- Meteorological Phenomena and Simulations
- Remote Sensing in Agriculture
- Solar Radiation and Photovoltaics
- Advanced Computational Techniques and Applications
- Advanced Algorithms and Applications
- Numerical methods for differential equations
- Remote Sensing and LiDAR Applications
- Matrix Theory and Algorithms
- Marine and coastal ecosystems
- Calibration and Measurement Techniques
- Cultural Industries and Urban Development
- Computational Fluid Dynamics and Aerodynamics
- Optical Systems and Laser Technology
- Advanced Optical Sensing Technologies
- Advanced Sensor and Control Systems
- Design Education and Practice
- Cardiac Imaging and Diagnostics
- Oceanographic and Atmospheric Processes
- Environmental Changes in China
- Regional Economic and Spatial Analysis
Langley Research Center
2013-2023
Science Systems and Applications (United States)
2016-2020
China Academy of Art
2018
Oak Ridge Associated Universities
2013-2014
Sinopec (China)
2014
Centre National de la Recherche Scientifique
2011-2013
Université de Lille
2013
Laboratoire d'Optique Atmosphérique
2010-2012
Nanjing University of Science and Technology
2009-2010
Chinese Academy of Sciences
1997-2000
Clouds cover about 70% of Earth's surface and play a dominant role in the energy water cycle our planet. Only satellite observations provide continuous survey state atmosphere over entire globe across wide range spatial temporal scales that compose weather climate variability. Satellite cloud data records now exceed more than 25 years; however, must be compiled from different datasets can exhibit systematic biases. Questions therefore arise as to accuracy limitations various sensors...
This article presents the GCM‐Oriented Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud Product (GOCCP) designed to evaluate cloudiness simulated by general circulation models (GCMs). For this purpose, with Orthogonal Polarization L1 data are processed following same steps as in a lidar simulator used diagnose model cloud cover that CALIPSO would observe from space if satellite was flying above an atmosphere similar predicted GCM. Instantaneous profiles of...
Abstract. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Operations (CALIPSO) mission released version 4.1 (V4) of their lidar level 2 cloud aerosol data products in November 2016. These new were derived from the CALIPSO V4 1 data, which calibration measured backscatter at both 532 1064 nm was significantly improved. This paper describes updates to cloud–aerosol discrimination (CAD) algorithm that more accurately differentiate between clouds aerosols throughout Earth's atmosphere....
Abstract The primary objective of the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission is to study climate impact clouds aerosols in atmosphere. However, recent studies have demonstrated that CALIPSO also collects information about ocean subsurface. this estimate subsurface backscatter from lidar measurements. effects receiver's transient response on attenuated were first removed order obtain correct profile. empirical relationship between sea surface wind...
Abstract. Cloud droplet number concentration (CDNC) is an important microphysical property of liquid clouds that impacts radiative forcing, precipitation and pivotal for understanding cloud–aerosol interactions. Current studies this parameter at global scales with satellite observations are still challenging, especially because retrieval algorithms developed passive sensors (i.e., MODerate Resolution Imaging Spectroradiometer (MODIS)/Aqua) have to rely on the assumption cloud adiabatic...
A new approach has been proposed to determine ocean subsurface particulate backscattering coefficient bbp from CALIOP 30° off-nadir lidar measurements. The method also provides estimates of the particle volume scattering function at 180° angle. based layer-integrated backscatter and coefficients are compared with results obtained MODIS color comparison analysis shows that can be accurately measurements, thereby supporting use space-borne measurements for studies.
Abstract. Cloud optical thickness (COT) is one of the most important parameter for characterization cloud in Earth radiative budget. Its retrieval strongly depends on instrument characteristics and many environment factors. Using coincident observations from POLDER/PARASOL MODIS/AQUA A-Train constellation, geographical distributions seasonal changes COT are presented, good agreement with general climatology characteristics. Retrieval uncertainties mainly associated to sensor spatial...
Abstract The Polarization and Anisotropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar (PARASOL) Aqua are two satellites on sun-synchronous orbits in the A-Train constellation. Aboard these platforms, Directionality Earth (POLDER) Moderate Resolution Imaging Spectroradiometer (MODIS) provide quasi simultaneous coincident observations cloud properties. similar but different detecting characteristics sensors call comparison between derived datasets to identify...
Abstract Phase transitions leading to cloud glaciation occur at temperatures that vary between 38°C and 0°C depending on aerosol types concentrations, the meteorology, microphysical macrophysical parameters, although relationships remain poorly understood. Here, we statistically retrieve a temperature from two passive space‐based instruments are part of NASA/CNES A‐Train, POLarization Directionality Earth's Reflectances (POLDER) MODerate resolution Imaging Spectroradiometer (MODIS). We...
The Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP), on-board the and Infrared Pathfinder Satellite Observations (CALIPSO) platform, is an elastic backscatter lidar that has been providing vertical profiles of spatial, optical, microphysical properties clouds aerosols since June 2006. Distinguishing between feature types (i.e., vs. aerosol) subtypes (e.g., ice water dust from smoke) in CALIOP measurements currently accomplished using layer-integrated acquired by co-polarized...
Abstract. This study applies fuzzy k-means (FKM) cluster analyses to a subset of the parameters reported in CALIPSO lidar level 2 data products order classify layers detected as either clouds or aerosols. The results obtained are used assess reliability cloud–aerosol discrimination (CAD) scores version 4.1 release products. FKM is an unsupervised learning algorithm, whereas operational CAD algorithm (COCA) takes highly supervised approach. Despite these substantial computational and...
The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), an instrument on the and Infrared Pathfinder Satellite Observations (CALIPSO), was operated as atmospheric lidar system to study impact of clouds aerosols Earth's radiation budget climate. This paper discusses receiver transient response CALIOP instrument, which is useful for getting a reliable attenuated backscatter profile from data products. noise tail effect (slow decaying rate) PMT broadening <br/> low-pass filter are both...
Abstract. The A-Train observations provide an unprecedented opportunity for the production of high quality dataset describing cloud properties. We illustrate in this study use one year coincident POLDER (Polarization and Directionality Earth Reflectance), MODIS (MODerate Resolution Imaging Spectroradiometer) CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) to establish a reference description top thermodynamic phase at global scale. present results extensive comparison between...
Since December 2004 the CNES PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar) mission has been flying in A-Train constellation. More than seven years data have routinely acquired processed by PARASOL/POLDER ground segment (CNES) ICARE Data Center Lille, France. PARASOL's unique spectral, directional polarization capabilities give powerful constraints to cloud retrieval scheme. They allow derivation classical properties...
Abstract The solution of the incompressible Navier‐Stokes equations in general two‐ and three‐dimensional domains using a multigrid method is considered. Because great variety boundary‐fitted grids may occur, robustness at premium. Therefore new ILU smoother called CILU (collective ILU) described, based on r‐transformations. In matrix that factorized block‐structured, with blocks corresponding to set physical variables. A algorithm as investigated. performance two three dimensions assessed...
Abstract. This study applies fuzzy K-means cluster analyses to a subset of the parameters reported in CALIPSO lidar level 2 data products and compares clustering results with cloud-aerosol discrimination (CAD) scores version 4.1 release products. The selection samples, training, performance measurements, linear discriminants, defuzzification, error propagation, key parameter feature type are discussed. Statistical show that classification agrees CAD algorithm for more than 94 % cases...
Abstract. Cloud droplet number concentration (CDNC) is an important microphysical property of liquid clouds that impacts radiative forcing, precipitation and it pivotal for understanding cloud-aerosols interactions. Current studies this parameter at global scales with satellite observations are still challenging, especially because retrieval algorithms developed passive sensors (i.e. MODIS/Aqua) have to rely on the assumption cloud adiabatic growth. The active sensor component A-Train...
Abstract. Cloud optical thickness (COT) is one of the most important parameter for characterization cloud in Earth radiative budget. Its retrieval strongly depends on instrument characteristics and many environment factors. Using coincident observations from POLDER/PARASOL MODIS/AQUA A-train constellation, geographical distributions seasonal changes COT are presented, good agreement with general climatology characteristics. Retrieval uncertainties mainly associated to sensor spatial...